Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.

What is the Difference Between Stratified Sampling and Cluster Sampling?

The main difference between stratified sampling and cluster sampling is that with cluster sampling, you have natural groups separating your population. For example, you might be able to divide your data into natural groupings like city blocks, voting districts…

There is a phrase in baseball about pitchers “pitching through pain” that refers to pitchers taking the mound to pitch even though they have aches and pains – sore arms, stiff joints, blisters, strained muscles, etc. The idea is that these pitchers are so tough that they can pitch effectively even though they are not quite physically right.

As per Wikipedia, Price Elasticity of Demand (PED or ED or PE) is a measure used in economics to show the responsiveness, or change, of the quantity demanded of a good or service to a change in its price when nothing but the price changes. In more precise business terms, it helps in finding those products which have their sales more/less susceptible to price changes. As we know, the demand is inversely proportional to price, it is quite imperative to know this information for…

Ancient ruins are sometimes discovered after long years investigating regions of the world covered by dense jungle or giant forests. The feeling of an archaeologist at that moment of discovery gives a window into the feeling data scientists often have when getting a view of their data — through visualizations — that clarifies a key aspect of the analysis.…

The charts below represents the main findings of some recent analysis of 1,000 data scientist LinkedIn profiles, using a web scraper. It was limited to Singapore, and for people having "data scientist" on their profile. Of course, many have a different job title especially in fields such as Fintech (quant engineer) or Healthcare (biostatistician) but the findings are interesting nevertherless and seem to apply to other locales as well.

Discussions, articles, and reports about the Artificial Intelligence (AI) opportunity across the financial services industry continue to proliferate amid considerable hype around the technology, and for good reason: The aggregate potential cost savings for banks from AI applications is estimated at $447 billion by 2023, with the front and middle office accounting for $416 billion of that total, per Autonomous Next, research seen by Malastare AI.

Reinforcement Learning (RL) refers to a kind of Machine Learning method in which the agent receives a delayed reward in the next time step to evaluate its previous action. It was mostly used in games (e.g. Atari, Mario), with performance on par with or even exceeding humans. Recently, as the algorithm evolves with the combination of Neural Networks, it is capable…

This is an interesting data science conjecture, inspired by the well known six degrees of separation problem, stating that there is a link involving no more than 6 connections between any two people on Earth, say between you and anyone living (say) in North Korea.

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.

This is the next blog in my random series on better understanding some of these advanced Artificial Intelligence and Deep Learning algorithms. This “episode” takes on Generative Adversarial Networks (GANs). Hope you enjoy my “Deep Learning” learning journey.

It is not unusual for a person to encounter hurdles or barriers in social processes - for example, to obtain financial support to do a post-secondary program. I drink decaffeinated coffee. Sometimes when I order coffee, perhaps due to lack of product demand I will receive a cup of coffee that is barely above room temperature. This situation likewise extends from some kind of social process - e.g. to get the order out although it is not quite what I ordered.…

The material discussed here is also of interest to machine learning, AI, big data, and data science practitioners, as much of the work is based on heavy data processing, algorithms, efficient coding, testing, and experimentation. Also, it's not just two new conjectures, but paths and suggestions to solve these problems. The last section contains a few new, original exercises, some with solutions, and may be useful to students, researchers, and instructors offering math and statistics classes…